How to Use the Billplz MCP in Pydantic AI

Stop silent payment failures with type-safe Billplz integrations in Pydantic AI.

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Connect Billplz MCP to Pydantic AI

Create your Vinkius account to connect Billplz to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Billplz with Pydantic AI

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Type-Safe Bill and Collection Management

Build bulletproof financial workflows where every Billplz response is validated at runtime using `get_bill`. When your Pydantic AI agent calls this or `list_collections`, the framework guarantees the returned data matches your schema exactly. If the API returns unexpected data, the system fails instantly instead of passing corrupt fields to your LLM. This keeps your billing pipeline predictable and free from hallucinated transaction amounts.

Strict Transaction Auditing via MCP Server

Use `list_transactions` to verify customer payments with absolute structural certainty. This MCP Server ensures that transaction IDs, amounts, and timestamps are parsed into strict Python types before your agent processes them. Your agent can safely run `get_bank_account` to verify destination details. You don't have to worry about missing or malformed fields because Pydantic AI will catch them before they reach your database.

Validated Lifecycle Actions

Safely modify your payment gateways using `activate_collection` and `deactivate_collection`. Because Pydantic AI validates the inputs, your agent cannot pass malformed collection IDs that might disrupt active payment routes. When cleaning up expired invoices, the agent uses `delete_bill` under strict type constraints. This prevents accidental deletions caused by the LLM generating incorrect parameters.

Setup guide

Set up Billplz MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "billplz-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Billplz tools.",
)

result = await agent.run("List recent Billplz transactions")
print(result.output)

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Common questions about Billplz MCP in Pydantic AI

Install the slim MCP package and use the unified MCPToolset helper pointing to your Vinkius HTTP URL. Pass this toolset directly to your Pydantic AI agent to start running validated payment operations.

The framework will throw a validation error immediately rather than letting your agent make decisions based on bad data. This prevents the LLM from hallucinating payment statuses when calling `get_bill`.

Yes, Pydantic AI enforces strict type checks on all tool arguments. When your agent attempts to execute `create_bill`, the framework validates the collection ID and amount format before the request ever leaves your server.

The integration is completely model-agnostic. You can use any supported LLM with your Pydantic AI agent to manage your bills and collections.

All data validation occurs in memory within an ephemeral V8 sandbox. Vinkius never logs or caches the contents of your bills, transaction logs, or bank accounts, keeping your financial operations private.

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